validation/test_code/03_MultitrialTestCode.R
In Sterniii3/drugdevelopR: Utility-Based Optimal Phase II/III Drug Development Planning
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.01", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 2, strategy = TRUE
)
# Strategies
expect_equal(res$Strategy, c(1, 2, 3, 23))
# Strategy 1
expect_equal(res[1,]$u, -1.89, tolerance = 0.005)
expect_equal(res[1,]$n2, 200)
expect_equal(res[1,]$n3, 238)
expect_equal(res[1,]$n, 438)
expect_equal(res[1,]$d2, 140)
expect_equal(res[1,]$d3, 167)
expect_equal(res[1,]$d, 307)
expect_equal(res[1,]$HRgo, 0.75)
# Strategy 2
expect_equal(res[2,]$u, -94.31, tolerance = 0.005)
expect_equal(res[2,]$n2, 172)
expect_equal(res[2,]$n3, 172)
expect_equal(res[2,]$n, 344)
expect_equal(res[2,]$d2, 120)
expect_equal(res[2,]$d3, 122)
expect_equal(res[2,]$d, 242)
expect_equal(res[2,]$HRgo, 0.72)
# Strategy 3
expect_equal(res[3,]$u, -12.88, tolerance = 0.005)
expect_equal(res[3,]$n2, 224)
expect_equal(res[3,]$n3, 252)
expect_equal(res[3,]$n, 476)
expect_equal(res[3,]$d2, 156)
expect_equal(res[3,]$d3, 177)
expect_equal(res[3,]$d, 333)
expect_equal(res[3,]$HRgo, 0.72)
# Strategy 23
expect_equal(res[4,]$u, 45.72, tolerance = 0.005)
expect_equal(res[4,]$n2, 178)
expect_equal(res[4,]$n3, 194)
expect_equal(res[4,]$n, 372)
expect_equal(res[4,]$d2, 124)
expect_equal(res[4,]$d3, 136)
expect_equal(res[4,]$d, 260)
expect_equal(res[4,]$HRgo, 0.73)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.02", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 3, strategy = 1
)
# Strategies
expect_equal(res$Strategy, 1)
expect_equal(res$u, -148.57, tolerance = 0.005)
expect_equal(res$n2, 160)
expect_equal(res$n3, 130)
expect_equal(res$n, 290)
expect_equal(res$HRgo, 0.67)
expect_equal(res$pgo, 0.2)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.03", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 2, strategy = TRUE,
K = 500
)
# Strategies
expect_equal(res$Strategy, c(1, 2, 3, 23))
# Strategy 1
expect_equal(res[1,]$u, -4.21, tolerance = 0.005)
expect_equal(res[1,]$n2, 172)
expect_equal(res[1,]$n3, 212)
expect_equal(res[1,]$n, 384)
expect_equal(res[1,]$K2, 229)
expect_equal(res[1,]$K3, 261)
expect_equal(res[1,]$HRgo, 0.74)
# Strategy 2
expect_equal(res[2,]$u, -94.31, tolerance = 0.005)
expect_equal(res[2,]$n2, 172)
expect_equal(res[2,]$n3, 172)
expect_equal(res[2,]$n, 344)
expect_equal(res[2,]$d2, 120)
expect_equal(res[2,]$d3, 122)
expect_equal(res[2,]$d, 242)
expect_equal(res[2,]$HRgo, 0.72)
# Strategy 3
expect_equal(res[3,]$u, -27.31, tolerance = 0.005)
expect_equal(res[3,]$n2, 172)
expect_equal(res[3,]$n3, 156)
expect_equal(res[3,]$n, 328)
expect_equal(res[3,]$K2, 229)
expect_equal(res[3,]$K3, 254)
expect_equal(res[3,]$HRgo, 0.68)
# Strategy 23
expect_equal(res[4,]$u, 45.72, tolerance = 0.005)
expect_equal(res[4,]$n2, 178)
expect_equal(res[4,]$n3, 194)
expect_equal(res[4,]$n, 372)
expect_equal(res[4,]$d2, 124)
expect_equal(res[4,]$d3, 136)
expect_equal(res[4,]$d, 260)
expect_equal(res[4,]$HRgo, 0.73)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.04", {
# Multi-trial time-to-event endpoints
expect_error({
optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 3, strategy = 2
)
})
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.05", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 200, d2max = 400, stepd2 = 4,
hrgomin = 0.8, hrgomax = 0.88, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
id1 = 210, id2 = 420,
case = 2, strategy = TRUE
)
# Strategies
expect_equal(res$Strategy, c(1, 2, 3, 23))
# Strategy 1
expect_equal(res[1,]$u, 1165.47, tolerance = 0.005)
expect_equal(res[1,]$n2, 424)
expect_equal(res[1,]$n3, 1044)
expect_equal(res[1,]$n, 1468)
expect_equal(res[1,]$d2, 296)
expect_equal(res[1,]$d3, 731)
expect_equal(res[1,]$d, 1027)
expect_equal(res[1,]$HRgo, 0.86)
# Strategy 2
expect_equal(res[2,]$u, 810.67, tolerance = 0.005)
expect_equal(res[2,]$n2, 384)
expect_equal(res[2,]$n3, 1040)
expect_equal(res[2,]$n, 1424)
expect_equal(res[2,]$d2, 268)
expect_equal(res[2,]$d3, 728)
expect_equal(res[2,]$d, 996)
expect_equal(res[2,]$HRgo, 0.85)
# Strategy 3
expect_equal(res[3,]$u, 1045.28, tolerance = 0.005)
expect_equal(res[3,]$n2, 446)
expect_equal(res[3,]$n3, 1398)
expect_equal(res[3,]$n, 1844)
expect_equal(res[3,]$d2, 312)
expect_equal(res[3,]$d3, 978)
expect_equal(res[3,]$d, 1290)
expect_equal(res[3,]$HRgo, 0.82)
# Strategy 23
expect_equal(res[4,]$u, -47.41, tolerance = 0.005)
expect_equal(res[4,]$n2, 286)
expect_equal(res[4,]$n3, 454)
expect_equal(res[4,]$n, 740)
expect_equal(res[4,]$d2, 200)
expect_equal(res[4,]$d3, 318)
expect_equal(res[4,]$d, 518)
expect_equal(res[4,]$HRgo, 0.80)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.06", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 20, d2max = 400, stepd2 = 2,
hrgomin = 0.65, hrgomax = 0.95, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 1, strategy = 1
)
# Strategies
expect_equal(res$Strategy, 1)
# Strategy 1
expect_equal(res$n2, 206) # optimal sample size in phase II
expect_equal(res$n3, 354) # resulting sample size in phase III
expect_equal(res$n, 560) # resulting total sample size
expect_equal(res$u, 432, tolerance = 0.05) # expected utility
expect_equal(res$HRgo, 0.84) # threshold for proceeding to phase III
expect_equal(res$d2, 144) # expected number of events in phase II
expect_equal(res$d3, 248) # expected number of events in phase III
expect_equal(res$d, 392) # total expected number of events
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.07", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.70, rrgomax = 0.80, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
in1 = 30, in2 = 60,
case = 3, strategy = TRUE,
)
# Strategies
expect_equal(res$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res[1,]$u, 405.56, tolerance = 0.005)
expect_equal(res[1,]$RRgo, 0.77)
expect_equal(res[1,]$n2, 176)
expect_equal(res[1,]$n3, 306)
expect_equal(res[1,]$n, 482)
# Strategy 3
expect_equal(res[2,]$u, 1494.31, tolerance = 0.005)
expect_equal(res[2,]$RRgo, 0.77)
expect_equal(res[2,]$n2, 340)
expect_equal(res[2,]$n3, 336)
expect_equal(res[2,]$n, 676)
# Strategy 4
expect_equal(res[3,]$u, 1736.36, tolerance = 0.005)
expect_equal(res[3,]$RRgo, 0.76)
expect_equal(res[3,]$n2, 384)
expect_equal(res[3,]$n3, 408)
expect_equal(res[3,]$n, 792)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.08", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 10, n2max = 400, stepn2 = 4,
rrgomin = 0.70, rrgomax = 0.80, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
in1 = 30, in2 = 60,
case = 2, strategy = 23,
)
# Strategies
expect_equal(res$Strategy, c(23))
expect_equal(res$u, 1701.93, tolerance = 0.005)
expect_equal(res$n2, 262)
expect_equal(res$n3, 224)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.09", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.80, rrgomax = 0.95, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
in1 = 30, in2 = 60,
case = 1, strategy = TRUE,
)
# Strategies
expect_equal(res$Strategy, c(1, 2))
# Strategy 1
expect_equal(res[1,]$u, 3187.57, tolerance = 0.005)
expect_equal(res[1,]$RRgo, 0.91)
expect_equal(res[1,]$n2, 176)
expect_equal(res[1,]$n3, 158)
expect_equal(res[1,]$n, 334)
# Strategy 2
expect_equal(res[2,]$u, 3657.57, tolerance = 0.005)
expect_equal(res[2,]$RRgo, 0.89)
expect_equal(res[2,]$n2, 240)
expect_equal(res[2,]$n3, 284)
expect_equal(res[2,]$n, 524)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.10", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.80, rrgomax = 0.95, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
in1 = 30, in2 = 60,
case = 2, strategy = 3,
)
res_constrained <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.80, rrgomax = 0.95, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
in1 = 30, in2 = 60,
case = 2, strategy = 3,
N = 600
)
# Unconstrained
expect_equal(res$Strategy, 3)
expect_equal(res$u, 2923.29, tolerance = 0.005)
expect_equal(res$n2, 288)
expect_equal(res$n3, 408)
expect_equal(res$n, 696)
# Constrained
expect_equal(res_constrained$u, 2795.38, tolerance = 0.005)
expect_equal(res_constrained$n2, 132)
expect_equal(res_constrained$n3, 468)
expect_equal(res_constrained$n, 600)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.11", {
# Multi-trial normal endpoints
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = FALSE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0.25, b = 0.75,
case = 3, strategy = TRUE,
)
# Strategies
expect_equal(res$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res[1,]$u, 1660.95, tolerance = 0.005)
expect_equal(res[1,]$Kappa, 0.16)
expect_equal(res[1,]$n2, 388)
expect_equal(res[1,]$n3, 666)
expect_equal(res[1,]$n, 1054)
expect_equal(res[1,]$sProg, 0.81)
# Strategy 3
expect_equal(res[2,]$u, 1282.14, tolerance = 0.005)
expect_equal(res[2,]$Kappa, 0.16)
expect_equal(res[2,]$n2, 332)
expect_equal(res[2,]$n3, 702)
expect_equal(res[2,]$n, 1034)
expect_equal(res[2,]$sProg, 0.67)
# Strategy 4
expect_equal(res[3,]$u, 1786.02, tolerance = 0.005)
expect_equal(res[3,]$Kappa, 0.18)
expect_equal(res[3,]$n2, 356)
expect_equal(res[3,]$n3, 888)
expect_equal(res[3,]$n, 1244)
expect_equal(res[3,]$sProg, 0.85)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.12", {
# Testing that parallel computing has an effect
start_time_3 = Sys.time()
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = FALSE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
)
end_time_3 = Sys.time()
time_elapsed_num_cl_3 = end_time_3 - start_time_3
start_time_1 = Sys.time()
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 6,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = FALSE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
)
end_time_1 = Sys.time()
time_elapsed_num_cl_1 = end_time_1 - start_time_1
expect_true(time_elapsed_num_cl_1 > time_elapsed_num_cl_3)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.13", {
# Multi-trial normal endpoints
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = TRUE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
)
res_prob_constraint <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = TRUE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
S = 0.82
)
# Unconstrained
expect_equal(res$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res[1, ]$u, 1514.35, tolerance = 0.005)
expect_equal(res[1, ]$Kappa, 0.16)
expect_equal(res[1, ]$n2, 440)
expect_equal(res[1, ]$n3, 830)
expect_equal(res[1, ]$n, 1270)
expect_equal(res[1, ]$sProg, 0.81)
# Strategy 3
expect_equal(res[2, ]$u, 1116.60, tolerance = 0.005)
expect_equal(res[2, ]$Kappa, 0.16)
expect_equal(res[2, ]$n2, 364)
expect_equal(res[2, ]$n3, 882)
expect_equal(res[2, ]$n, 1246)
expect_equal(res[2, ]$sProg, 0.68)
# Strategy 4
expect_equal(res[3, ]$u, 1395.35, tolerance = 0.005)
expect_equal(res[3, ]$Kappa, 0.18)
expect_equal(res[3, ]$n2, 424)
expect_equal(res[3, ]$n3, 1128)
expect_equal(res[3, ]$n, 1552)
expect_equal(res[3, ]$sProg, 0.86)
# Constrained
expect_equal(res_prob_constraint$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res_prob_constraint[1, ]$u, 1513.26, tolerance = 0.005)
expect_equal(res_prob_constraint[1, ]$Kappa, 0.14)
expect_equal(res_prob_constraint[1, ]$n2, 444)
expect_equal(res_prob_constraint[1, ]$n3, 852)
expect_equal(res_prob_constraint[1, ]$n, 1296)
expect_equal(res_prob_constraint[1, ]$sProg, 0.82)
# Strategy 3
expect_equal(res_prob_constraint[2, ]$u, -9999)
# Strategy 4
expect_equal(res_prob_constraint[3, ]$u, 1395.35, tolerance = 0.005)
expect_equal(res_prob_constraint[3, ]$Kappa, 0.18)
expect_equal(res_prob_constraint[3, ]$n2, 424)
expect_equal(res_prob_constraint[3, ]$n3, 1128)
expect_equal(res_prob_constraint[3, ]$n, 1552)
expect_equal(res_prob_constraint[3, ]$sProg, 0.86)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.14", {
# Multi-trial normal endpoints
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = TRUE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 2, strategy = 3,
)
# Strategy 1
expect_equal(res$u, 1749.97, tolerance = 0.005)
expect_equal(res$Kappa, 0.16)
expect_equal(res$n2, 416)
expect_equal(res$n3, 876)
expect_equal(res$n, 1292)
})
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#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.01", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 2, strategy = TRUE
)
# Strategies
expect_equal(res$Strategy, c(1, 2, 3, 23))
# Strategy 1
expect_equal(res[1,]$u, -1.89, tolerance = 0.005)
expect_equal(res[1,]$n2, 200)
expect_equal(res[1,]$n3, 238)
expect_equal(res[1,]$n, 438)
expect_equal(res[1,]$d2, 140)
expect_equal(res[1,]$d3, 167)
expect_equal(res[1,]$d, 307)
expect_equal(res[1,]$HRgo, 0.75)
# Strategy 2
expect_equal(res[2,]$u, -94.31, tolerance = 0.005)
expect_equal(res[2,]$n2, 172)
expect_equal(res[2,]$n3, 172)
expect_equal(res[2,]$n, 344)
expect_equal(res[2,]$d2, 120)
expect_equal(res[2,]$d3, 122)
expect_equal(res[2,]$d, 242)
expect_equal(res[2,]$HRgo, 0.72)
# Strategy 3
expect_equal(res[3,]$u, -12.88, tolerance = 0.005)
expect_equal(res[3,]$n2, 224)
expect_equal(res[3,]$n3, 252)
expect_equal(res[3,]$n, 476)
expect_equal(res[3,]$d2, 156)
expect_equal(res[3,]$d3, 177)
expect_equal(res[3,]$d, 333)
expect_equal(res[3,]$HRgo, 0.72)
# Strategy 23
expect_equal(res[4,]$u, 45.72, tolerance = 0.005)
expect_equal(res[4,]$n2, 178)
expect_equal(res[4,]$n3, 194)
expect_equal(res[4,]$n, 372)
expect_equal(res[4,]$d2, 124)
expect_equal(res[4,]$d3, 136)
expect_equal(res[4,]$d, 260)
expect_equal(res[4,]$HRgo, 0.73)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.02", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 3, strategy = 1
)
# Strategies
expect_equal(res$Strategy, 1)
expect_equal(res$u, -148.57, tolerance = 0.005)
expect_equal(res$n2, 160)
expect_equal(res$n3, 130)
expect_equal(res$n, 290)
expect_equal(res$HRgo, 0.67)
expect_equal(res$pgo, 0.2)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.03", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 2, strategy = TRUE,
K = 500
)
# Strategies
expect_equal(res$Strategy, c(1, 2, 3, 23))
# Strategy 1
expect_equal(res[1,]$u, -4.21, tolerance = 0.005)
expect_equal(res[1,]$n2, 172)
expect_equal(res[1,]$n3, 212)
expect_equal(res[1,]$n, 384)
expect_equal(res[1,]$K2, 229)
expect_equal(res[1,]$K3, 261)
expect_equal(res[1,]$HRgo, 0.74)
# Strategy 2
expect_equal(res[2,]$u, -94.31, tolerance = 0.005)
expect_equal(res[2,]$n2, 172)
expect_equal(res[2,]$n3, 172)
expect_equal(res[2,]$n, 344)
expect_equal(res[2,]$d2, 120)
expect_equal(res[2,]$d3, 122)
expect_equal(res[2,]$d, 242)
expect_equal(res[2,]$HRgo, 0.72)
# Strategy 3
expect_equal(res[3,]$u, -27.31, tolerance = 0.005)
expect_equal(res[3,]$n2, 172)
expect_equal(res[3,]$n3, 156)
expect_equal(res[3,]$n, 328)
expect_equal(res[3,]$K2, 229)
expect_equal(res[3,]$K3, 254)
expect_equal(res[3,]$HRgo, 0.68)
# Strategy 23
expect_equal(res[4,]$u, 45.72, tolerance = 0.005)
expect_equal(res[4,]$n2, 178)
expect_equal(res[4,]$n3, 194)
expect_equal(res[4,]$n, 372)
expect_equal(res[4,]$d2, 124)
expect_equal(res[4,]$d3, 136)
expect_equal(res[4,]$d, 260)
expect_equal(res[4,]$HRgo, 0.73)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.04", {
# Multi-trial time-to-event endpoints
expect_error({
optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 100, d2max = 300, stepd2 = 4,
hrgomin = 0.65, hrgomax = 0.8, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 3, strategy = 2
)
})
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.05", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 200, d2max = 400, stepd2 = 4,
hrgomin = 0.8, hrgomax = 0.88, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
id1 = 210, id2 = 420,
case = 2, strategy = TRUE
)
# Strategies
expect_equal(res$Strategy, c(1, 2, 3, 23))
# Strategy 1
expect_equal(res[1,]$u, 1165.47, tolerance = 0.005)
expect_equal(res[1,]$n2, 424)
expect_equal(res[1,]$n3, 1044)
expect_equal(res[1,]$n, 1468)
expect_equal(res[1,]$d2, 296)
expect_equal(res[1,]$d3, 731)
expect_equal(res[1,]$d, 1027)
expect_equal(res[1,]$HRgo, 0.86)
# Strategy 2
expect_equal(res[2,]$u, 810.67, tolerance = 0.005)
expect_equal(res[2,]$n2, 384)
expect_equal(res[2,]$n3, 1040)
expect_equal(res[2,]$n, 1424)
expect_equal(res[2,]$d2, 268)
expect_equal(res[2,]$d3, 728)
expect_equal(res[2,]$d, 996)
expect_equal(res[2,]$HRgo, 0.85)
# Strategy 3
expect_equal(res[3,]$u, 1045.28, tolerance = 0.005)
expect_equal(res[3,]$n2, 446)
expect_equal(res[3,]$n3, 1398)
expect_equal(res[3,]$n, 1844)
expect_equal(res[3,]$d2, 312)
expect_equal(res[3,]$d3, 978)
expect_equal(res[3,]$d, 1290)
expect_equal(res[3,]$HRgo, 0.82)
# Strategy 23
expect_equal(res[4,]$u, -47.41, tolerance = 0.005)
expect_equal(res[4,]$n2, 286)
expect_equal(res[4,]$n3, 454)
expect_equal(res[4,]$n, 740)
expect_equal(res[4,]$d2, 200)
expect_equal(res[4,]$d3, 318)
expect_equal(res[4,]$d, 518)
expect_equal(res[4,]$HRgo, 0.80)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.06", {
# Multi-trial time-to-event endpoints
res <- optimal_multitrial(alpha = 0.025,
beta = 0.1,
hr1 = 0.69, hr2 = 0.88,
xi2 = 0.7, xi3 = 0.7,
d2min = 20, d2max = 400, stepd2 = 2,
hrgomin = 0.65, hrgomax = 0.95, stephrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
id1 = 210, id2 = 420,
case = 1, strategy = 1
)
# Strategies
expect_equal(res$Strategy, 1)
# Strategy 1
expect_equal(res$n2, 206) # optimal sample size in phase II
expect_equal(res$n3, 354) # resulting sample size in phase III
expect_equal(res$n, 560) # resulting total sample size
expect_equal(res$u, 432, tolerance = 0.05) # expected utility
expect_equal(res$HRgo, 0.84) # threshold for proceeding to phase III
expect_equal(res$d2, 144) # expected number of events in phase II
expect_equal(res$d3, 248) # expected number of events in phase III
expect_equal(res$d, 392) # total expected number of events
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.07", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.70, rrgomax = 0.80, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
in1 = 30, in2 = 60,
case = 3, strategy = TRUE,
)
# Strategies
expect_equal(res$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res[1,]$u, 405.56, tolerance = 0.005)
expect_equal(res[1,]$RRgo, 0.77)
expect_equal(res[1,]$n2, 176)
expect_equal(res[1,]$n3, 306)
expect_equal(res[1,]$n, 482)
# Strategy 3
expect_equal(res[2,]$u, 1494.31, tolerance = 0.005)
expect_equal(res[2,]$RRgo, 0.77)
expect_equal(res[2,]$n2, 340)
expect_equal(res[2,]$n3, 336)
expect_equal(res[2,]$n, 676)
# Strategy 4
expect_equal(res[3,]$u, 1736.36, tolerance = 0.005)
expect_equal(res[3,]$RRgo, 0.76)
expect_equal(res[3,]$n2, 384)
expect_equal(res[3,]$n3, 408)
expect_equal(res[3,]$n, 792)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.08", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 10, n2max = 400, stepn2 = 4,
rrgomin = 0.70, rrgomax = 0.80, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
w = 0.3,
in1 = 30, in2 = 60,
case = 2, strategy = 23,
)
# Strategies
expect_equal(res$Strategy, c(23))
expect_equal(res$u, 1701.93, tolerance = 0.005)
expect_equal(res$n2, 262)
expect_equal(res$n3, 224)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.09", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.80, rrgomax = 0.95, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
in1 = 30, in2 = 60,
case = 1, strategy = TRUE,
)
# Strategies
expect_equal(res$Strategy, c(1, 2))
# Strategy 1
expect_equal(res[1,]$u, 3187.57, tolerance = 0.005)
expect_equal(res[1,]$RRgo, 0.91)
expect_equal(res[1,]$n2, 176)
expect_equal(res[1,]$n3, 158)
expect_equal(res[1,]$n, 334)
# Strategy 2
expect_equal(res[2,]$u, 3657.57, tolerance = 0.005)
expect_equal(res[2,]$RRgo, 0.89)
expect_equal(res[2,]$n2, 240)
expect_equal(res[2,]$n3, 284)
expect_equal(res[2,]$n, 524)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.10", {
# Multi-trial binary endpoints
res <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.80, rrgomax = 0.95, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
in1 = 30, in2 = 60,
case = 2, strategy = 3,
)
res_constrained <- optimal_multitrial_binary(alpha = 0.025,
beta = 0.1,
p0 = 0.6, p11 = 0.3, p12 = 0.5,
n2min = 100, n2max = 400, stepn2 = 4,
rrgomin = 0.80, rrgomax = 0.95, steprrgo = 0.01,
b1 = 1000, b2 = 3000, b3 = 5000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
w = 0.3,
in1 = 30, in2 = 60,
case = 2, strategy = 3,
N = 600
)
# Unconstrained
expect_equal(res$Strategy, 3)
expect_equal(res$u, 2923.29, tolerance = 0.005)
expect_equal(res$n2, 288)
expect_equal(res$n3, 408)
expect_equal(res$n, 696)
# Constrained
expect_equal(res_constrained$u, 2795.38, tolerance = 0.005)
expect_equal(res_constrained$n2, 132)
expect_equal(res_constrained$n3, 468)
expect_equal(res_constrained$n, 600)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.11", {
# Multi-trial normal endpoints
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = FALSE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0.25, b = 0.75,
case = 3, strategy = TRUE,
)
# Strategies
expect_equal(res$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res[1,]$u, 1660.95, tolerance = 0.005)
expect_equal(res[1,]$Kappa, 0.16)
expect_equal(res[1,]$n2, 388)
expect_equal(res[1,]$n3, 666)
expect_equal(res[1,]$n, 1054)
expect_equal(res[1,]$sProg, 0.81)
# Strategy 3
expect_equal(res[2,]$u, 1282.14, tolerance = 0.005)
expect_equal(res[2,]$Kappa, 0.16)
expect_equal(res[2,]$n2, 332)
expect_equal(res[2,]$n3, 702)
expect_equal(res[2,]$n, 1034)
expect_equal(res[2,]$sProg, 0.67)
# Strategy 4
expect_equal(res[3,]$u, 1786.02, tolerance = 0.005)
expect_equal(res[3,]$Kappa, 0.18)
expect_equal(res[3,]$n2, 356)
expect_equal(res[3,]$n3, 888)
expect_equal(res[3,]$n, 1244)
expect_equal(res[3,]$sProg, 0.85)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.12", {
# Testing that parallel computing has an effect
start_time_3 = Sys.time()
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = FALSE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
)
end_time_3 = Sys.time()
time_elapsed_num_cl_3 = end_time_3 - start_time_3
start_time_1 = Sys.time()
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 6,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = FALSE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
)
end_time_1 = Sys.time()
time_elapsed_num_cl_1 = end_time_1 - start_time_1
expect_true(time_elapsed_num_cl_1 > time_elapsed_num_cl_3)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.13", {
# Multi-trial normal endpoints
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = TRUE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
)
res_prob_constraint <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = TRUE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 3, strategy = TRUE,
S = 0.82
)
# Unconstrained
expect_equal(res$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res[1, ]$u, 1514.35, tolerance = 0.005)
expect_equal(res[1, ]$Kappa, 0.16)
expect_equal(res[1, ]$n2, 440)
expect_equal(res[1, ]$n3, 830)
expect_equal(res[1, ]$n, 1270)
expect_equal(res[1, ]$sProg, 0.81)
# Strategy 3
expect_equal(res[2, ]$u, 1116.60, tolerance = 0.005)
expect_equal(res[2, ]$Kappa, 0.16)
expect_equal(res[2, ]$n2, 364)
expect_equal(res[2, ]$n3, 882)
expect_equal(res[2, ]$n, 1246)
expect_equal(res[2, ]$sProg, 0.68)
# Strategy 4
expect_equal(res[3, ]$u, 1395.35, tolerance = 0.005)
expect_equal(res[3, ]$Kappa, 0.18)
expect_equal(res[3, ]$n2, 424)
expect_equal(res[3, ]$n3, 1128)
expect_equal(res[3, ]$n, 1552)
expect_equal(res[3, ]$sProg, 0.86)
# Constrained
expect_equal(res_prob_constraint$Strategy, c(1, 3, 4))
# Strategy 1
expect_equal(res_prob_constraint[1, ]$u, 1513.26, tolerance = 0.005)
expect_equal(res_prob_constraint[1, ]$Kappa, 0.14)
expect_equal(res_prob_constraint[1, ]$n2, 444)
expect_equal(res_prob_constraint[1, ]$n3, 852)
expect_equal(res_prob_constraint[1, ]$n, 1296)
expect_equal(res_prob_constraint[1, ]$sProg, 0.82)
# Strategy 3
expect_equal(res_prob_constraint[2, ]$u, -9999)
# Strategy 4
expect_equal(res_prob_constraint[3, ]$u, 1395.35, tolerance = 0.005)
expect_equal(res_prob_constraint[3, ]$Kappa, 0.18)
expect_equal(res_prob_constraint[3, ]$n2, 424)
expect_equal(res_prob_constraint[3, ]$n3, 1128)
expect_equal(res_prob_constraint[3, ]$n, 1552)
expect_equal(res_prob_constraint[3, ]$sProg, 0.86)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-23
test_that("03.14", {
# Multi-trial normal endpoints
res <- optimal_multitrial_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.375, Delta = 0.5,
n2min = 200, n2max = 500, stepn2 = 4,
kappamin = 0.1, kappamax = 0.2, stepkappa = 0.02,
b1 = 3000, b2 = 8000, b3 = 10000,
num_cl = 12,
c02 = 15, c03 = 20,
c2 = 0.675, c3 = 0.72,
fixed = TRUE,
w = 0.5,
in1 = 300, in2 = 600,
a = 0, b = 0.75,
case = 2, strategy = 3,
)
# Strategy 1
expect_equal(res$u, 1749.97, tolerance = 0.005)
expect_equal(res$Kappa, 0.16)
expect_equal(res$n2, 416)
expect_equal(res$n3, 876)
expect_equal(res$n, 1292)
})
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